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Record W2061177460 · doi:10.1002/joc.1796

Downscaled GCM projections of winter and summer mass balance for Peyto Glacier, Alberta, Canada (2000–2100) from ensemble simulations with ECHAM5‐MPIOM

2008· article· en· W2061177460 on OpenAlexafffundabout
Christoph Matulla, Emma Watson, Sebastian Wagner, Wolfgang Schöner

Bibliographic record

VenueInternational Journal of Climatology · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsEnvironment and Climate Change Canada
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsClimatologyGlacierGlacier mass balanceEnvironmental scienceGCM transcription factorsDownscalingGeneral Circulation ModelClimate changeRepresentative Concentration PathwaysAltitude (triangle)Atmospheric circulationAtmospheric sciencesGeologyGeographyPhysical geographyMathematics

Abstract

fetched live from OpenAlex

Abstract We apply a direct downscaling approach to generate ensembles of local‐scale glacier mass balance projections from coarse‐scale general circulation model (GCM) data. The general modes of the atmospheric circulation over a large geographical region are linked statistically to Peyto Glacier's winter and summer balance separately. Our study focuses on the generation of ensemble projections derived from simulations with ECHAM5‐MPIOM forced with Intergovernmental Panel on Climate Change ‐ Special Report on Emission Scenarios (IPCC‐SRES) A1B and B1. The resulting ensembles of mass balance projections show a moderate increase in winter balance and a steep decrease in summer balance. Together these results suggest continued frontal recession and downwasting of Peyto Glacier and a shift of the equilibrium line altitude by at least 100 m above that estimated for the 1966–2001 period suggesting that very little of the glacier will remain by 2100. Copyright © 2008 Crown in the right of Canada. Published by John Wiley & Sons, Ltd.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.136
Threshold uncertainty score0.274

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.238
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations12
Published2008
Admission routes3
Has abstractyes

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